Deutsches Zentrum für Herzinsuffizienz (DZHI)
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Sonstige beteiligte Institutionen
- Clinical Trial Center (CTC) / Zentrale für Klinische Studien Würzburg (ZKSW) (2)
- Center for Interdisciplinary Clinical Research, Würzburg University, Würzburg, Germany (1)
- Datenintegrationszentrum Würzburg (DIZ) (1)
- Department of Medicinal Chemistry, University of Vienna, Althanstraße 14, 1090 Vienna, Austria (1)
- Department of Pharmaceutical Technology and Biopharmaceutics, University of Vienna, Althanstraße 14, 1090 Vienna, Austria (1)
- Interdisziplinäre Biomaterial- und Datenbank Würzburg (ibdw) (1)
- Interdisziplinäre Zentrum für Klinische Forschung (IZKF) (1)
- Klinische Studienzentrale (Universitätsklinikum) (1)
- Servicezentrum Medizin-Informatik (1)
- Universitätsklinikum Würzburg (UKW) (1)
Aims
This study aimed to identify echocardiographic determinants of left ventricular thrombus (LVT) formation after acute anterior myocardial infarction (MI).
Methods and results
This case–control study comprised 55 acute anterior MI patients with LVT as cases and 55 acute anterior MI patients without LVT as controls, who were selected from a cohort of consecutive patients with ischemic heart failure in our hospital. The cases and controls were matched for age, sex, and left ventricular ejection fraction. LVT was detected by routine/contrast echocardiography or cardiac magnetic resonance imaging during the first 3 months following MI. Formation of apical aneurysm after MI was independently associated with LVT formation [72.0% vs. 43.5%, odds ratio (OR) = 5.06, 95% confidence interval (CI) 1.65–15.48, P = 0.005]. Echocardiographic risk factors associated with LVT formation included reduced mitral annular plane systolic excursion (<7 mm, OR = 4.69, 95% CI 1.84–11.95, P = 0.001), moderate–severe diastolic dysfunction (OR = 2.71, 95% CI 1.11–6.57, P = 0.028), and right ventricular (RV) dysfunction [reduced tricuspid annular plane systolic excursion < 17 mm (OR = 5.48, 95% CI 2.12–14.13, P < 0.001), reduced RV fractional area change < 0.35 (OR = 3.32, 95% CI 1.20–9.18, P = 0.021), and enlarged RV mid diameter (per 5 mm increase OR = 1.62, 95% CI 1.12–2.34, P = 0.010)]. Reduced tricuspid annular plane systolic excursion (<17 mm) significantly associated with increased risk of LVT in anterior MI patients (OR = 3.84, 95% CI 1.37–10.75, P = 0.010), especially in those patients without apical aneurysm (OR = 5.12, 95% CI 1.45–18.08, P = 0.011), independent of body mass index, hypertension, anaemia, mitral annular plane systolic excursion, and moderate–severe diastolic dysfunction.
Conclusions
Right ventricular dysfunction as determined by reduced TAPSE or RV fractional area change is independently associated with LVT formation in acute anterior MI patients, especially in the setting of MI patients without the formation of an apical aneurysm. This study suggests that besides assessment of left ventricular abnormalities, assessment of concomitant RV dysfunction is of importance on risk stratification of LVT formation in patients with acute anterior MI.
A deep integration of routine care and research remains challenging in many respects. We aimed to show the feasibility of an automated transformation and transfer process feeding deeply structured data with a high level of granularity collected for a clinical prospective cohort study from our hospital information system to the study's electronic data capture system, while accounting for study-specific data and visits. We developed a system integrating all necessary software and organizational processes then used in the study. The process and key system components are described together with descriptive statistics to show its feasibility in general and to identify individual challenges in particular. Data of 2051 patients enrolled between 2014 and 2020 was transferred. We were able to automate the transfer of approximately 11 million individual data values, representing 95% of all entered study data. These were recorded in n = 314 variables (28% of all variables), with some variables being used multiple times for follow-up visits. Our validation approach allowed for constant good data quality over the course of the study. In conclusion, the automated transfer of multi-dimensional routine medical data from HIS to study databases using specific study data and visit structures is complex, yet viable.
Stem cell therapy holds great promise for tissue regeneration and cancer treatment, although its efficacy is still inconclusive and requires further understanding and optimization of the procedures. Non-invasive cell tracking can provide an important opportunity to monitor in vivo cell distribution in living subjects. Here, using a combination of positron emission tomography (PET) and in vitro 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) direct cell labelling, the feasibility of engrafted stem cell monitoring was tested in multiple animal species. Human mesenchymal stem cells (MSCs) were incubated with phosphate-buffered saline containing [18F]FDG for in vitro cell radiolabelling. The pre-labelled MSCs were administrated via peripheral vein in a mouse (n=1), rats (n=4), rabbits (n=4) and non-human primates (n=3), via carotid artery in rats (n=4) and non-human primates (n=3), and via intra-myocardial injection in rats (n=5). PET imaging was started 10 min after cell administration using a dedicated small animal PET system for a mouse and rats. A clinical PET system was used for the imaging of rabbits and non-human primates. After MSC administration via peripheral vein, PET imaging revealed intense radiotracer signal from the lung in all tested animal species including mouse, rat, rabbit, and non-human primate, suggesting administrated MSCs were trapped in the lung tissue. Furthermore, the distribution of the PET signal significantly differed based on the route of cell administration. Administration via carotid artery showed the highest activity in the head, and intra-myocardial injection increased signal from the heart. In vitro [18F]FDG MSC pre-labelling for PET imaging is feasible and allows non-invasive visualization of initial cell distribution after different routes of cell administration in multiple animal models. Those results highlight the potential use of that imaging approach for the understanding and optimization of stem cell therapy in translational research.
Fibroblasts isolated from a skin biopsy of a healthy 46-year-old female were infected with Sendai virus containing the Yamanaka factors to produce transgene-free human induced pluripotent stem cells (iPSCs). CRISPR/Cas9 was used to generate isogenic cell lines with a gene dose-dependent deficiency of CDH13, a risk gene associated with neurodevelopmental and psychiatric disorders. Thereby, a heterozygous CDH13 knockout (CDH13\(^{+/-}\)) and a CDH13 null mutant (CDH13\(^{-/-}\)) iPSC line was obtained. All three lines showed expression of pluripotency-associated markers, the ability to differentiate into cells of the three germ layers in vitro, and a normal female karyotype.
In recent years, a paradigm shift from single-photon-emitting radionuclide radiotracers toward positron-emission tomography (PET) radiotracers has occurred in nuclear oncology. Although PET-based molecular imaging of the kidneys is still in its infancy, such a trend has emerged in the field of functional renal radionuclide imaging. Potentially allowing for precise and thorough evaluation of renal radiotracer urodynamics, PET radionuclide imaging has numerous advantages including precise anatomical co-registration with CT images and dynamic three-dimensional imaging capability. In addition, relative to scintigraphic approaches, PET can allow for significantly reduced scan time enabling high-throughput in a busy PET practice and further reduces radiation exposure, which may have a clinical impact in pediatric populations. In recent years, multiple renal PET radiotracers labeled with C-11, Ga-68, and F-18 have been utilized in clinical studies. Beyond providing a precise non-invasive read-out of renal function, such radiotracers may also be used to assess renal inflammation. This manuscript will provide an overview of renal molecular PET imaging and will highlight the transformation of conventional scintigraphy of the kidneys toward novel, high-resolution PET imaging for assessing renal function. In addition, future applications will be introduced, e.g. by transferring the concept of molecular image-guided diagnostics and therapy (theranostics) to the field of nephrology.
Arrhythmogenic cardiomyopathy (ACM) is characterized by fibro-fatty replacement of the myocardium, heart failure and life-threatening ventricular arrhythmias. Causal mutations were identified in genes encoding for proteins of the desmosomes, predominantly plakophilin-2 (PKP2) and desmoglein-2 (DSG2). We generated gene-edited knock-out iPSC lines for PKP2 (JMUi001-A-2) and DSG2 (JMUi001-A-3) using the CRISPR/Cas9 system in a healthy control iPSC background (JMUi001A). Stem cell-like morphology, robust expression of pluripotency markers, embryoid body formation and normal karyotypes confirmed the generation of high quality iPSCs to provide a novel isogenic human in vitro model system mimicking ACM when differentiated into cardiomyocytes.
Background
Right ventricular dysfunction after CABG is associated with poor peri- and postoperative outcomes. We aimed to identify clinical and experimental predictors for preoperative inapparent right ventricular dysfunction and therefore hypothesized that reduced myofilament force development as well as altered levels of biomarkers might predict inapparent right ventricular dysfunction.
Methods
From 08/2016 to 02/2018, 218 patients scheduled for CABG were divided into two groups (TAPSE ≥ 20 mm, n = 178; TAPSE < 20 mm, n = 40). Baseline serum samples for biomarkers (Galectin, TGFß1, N Acyl-SDMA, Arginine, ADMA and Pentraxin-3), clinical laboratory and transthoracic echocardiographic parameters were evaluated. To examine the myocardial apparatus of the right ventricle intraoperative right auricular tissue was harvested for stepwise skinned fiber force measurements.
Results
Patients with TAPSE < 20 mm had a higher incidence of DM (55 vs. 34%, p = 0.018), preoperative AFib (43 vs. 16%, p < 0.001), reduced GFR (67 ± 18 vs. 77 ± 24 ml/min/1.73 m\(^2\), p = 0.013), larger LA area (22 ± 6 vs. 20 ± 5 cm\(^2\), p = 0.005) and reduced LVEF (50 vs. 55%, p = 0.008). Furthermore, higher serum ADMA (0.70 ± 0.13 vs. 0.65 ± 0.15 µmol/l, p = 0.046) and higher serum Pentraxin-3 levels (3371 ± 1068 vs. 2681 ± 1353 pg/dl, p = 0.004) were observed in these patients. Skinned fiber force measurements showed significant lower values at almost every step of calcium concentration (pCa 4.52 to pCa 5.5, p < 0.01 and pCa 5.75–6.0, p < 0.05). Multivariable analysis revealed DM (OR 2.53, CI 1.12–5.73, Euro Score II (OR 1.34, CI 1.02–1.78), preoperative AF (OR 4.86, CI 2.06–11.47), GFR (OR 7.72, CI 1.87–31.96), albumin (OR 1.56, CI 0.52–2.60), Pentraxin-3 (OR 19.68, CI 14.13–25.24), depressed LVEF (OR 8.61, CI 6.37–10.86), lower force values: (pCa 5.4; OR 2.34, CI 0.40–4.29 and pCa 5.2; OR 2.00, CI 0.39–3.60) as predictors for clinical inapparent right heart dysfunction.
Conclusions
These preliminary data showed that inapparent right heart dysfunction in CAD is already associated with reduced force development of the contractile apparatus.
Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI
(2021)
Background
Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance.
Results
We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model.
Conclusions
Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.
Aims
It has been hypothesized that cardiac decompensation accompanying acute heart failure (AHF) episodes generates a pro-inflammatory environment boosting an adaptive immune response against myocardial antigens, thus contributing to progression of heart failure (HF) and poor prognosis. We assessed the prevalence of anti-myocardial autoantibodies (AMyA) as biomarkers reflecting adaptive immune responses in patients admitted to the hospital for AHF, followed the change in AMyA titres for 6 months after discharge, and evaluated their prognostic utility.
Methods and results
AMyA were determined in n = 47 patients, median age 71 (quartiles 60; 80) years, 23 (49%) female, and 24 (51%) with HF with preserved ejection fraction, from blood collected at baseline (time point of hospitalization) and at 6 month follow-up (visit F6). Patients were followed for 18 months (visit F18). The prevalence of AMyA increased from baseline (n = 21, 45%) to F6 (n = 36, 77%; P < 0.001). At F6, the prevalence of AMyA was higher in patients with HF with preserved ejection fraction (n = 21, 88%) compared with patients with reduced ejection fraction (n = 14, 61%; P = 0.036). During the subsequent 12 months after F6, that is up to F18, patients with newly developed AMyA at F6 had a higher risk for the combined endpoint of death or rehospitalization for HF (hazard ratio 4.79, 95% confidence interval 1.13–20.21; P = 0.033) compared with patients with persistent or without AMyA at F6.
Conclusions
Our results support the hypothesis that AHF may induce patterns of adaptive immune responses. More studies in larger populations and well-defined patient subgroups are needed to further clarify the role of the adaptive immune system in HF progression.